During third week I’ve read some docs and watch some videos about organizations that are using learning analytics to improve their achievement.
Basically, they are using LA to dig on to their data and localize the areas they need to attend in deep or to diagnose the studentens trying to foresee their probabilities of success (mainly to diagnose students in risk of fail).
One thing very important is a basic consideration that organizations needs to rethink BEFORE doing anything: Wich is the value of the student fail?
Some high education institutions, like the ones we have in Spain, consider some degree of fail. Some teachers participates on this idea on the believe that a high level of educational quality and proficiency entails high levels of students failure. A lot of “failings” means that the requirements are hard to achieve and not all the students are capable of this: subliminally they conceive teaching as selection process instead of elevation process.
But nowdays, immersed in a economic crisis that are forcing to rethink what we are doing in Universities, we can’t afford such high levels of fails. Every student counts. The public (and private!) money is forced to be spent in a better and more efficient way. And it is necessary to check the failing causes and to correct them.
In that sens, the case studies web have read about are very enlightening. Those institutions worried about how to help students to achieve high levels of proficiency detects which of them are in risk of fail and points the efforts on those problems. An example to follow.